Fixed bugs in relative_TT_residuals_plotter

.gitignore

@@ -89,3 +89,4 @@ seismic/xcorqc/**/*.pbs
 **/junk.*
 **/LOG_CODE_DUPES_*.txt
 **/LOG_LOCATION_DUPES_*.txt
+/seismic/gps_corrections/p_combined.txt

seismic/gps_corrections/gps_clock_correction_gui.py

@@ -143,7 +143,7 @@ def _update_next_button(self, *_unused):
         nc_file_value = self.nc_file.get()
         nc_file_valid = bool(nc_file_value) and os.path.isfile(nc_file_value)
         if nc_file_valid:
-            self.station_code= self._extract_code_from_filename(nc_file_value)
+            self.station_code = self._extract_code_from_filename(nc_file_value)
         else:
             self.station_code = ''
         self.stn_code_label['text'] = "Station code: " + self.station_code

seismic/gps_corrections/relative_tt_residuals_plotter.py

@@ -33,10 +33,7 @@
 else:
     import pathlib  # pylint: disable=import-error
 
-from seismic.gps_corrections.picks_reader_utils import (read_picks_ensemble,
-                                                        get_network_stations,
-                                                        compute_matching_network_mask,
-                                                        generate_large_events_catalog)
+from seismic.gps_corrections.picks_reader_utils import (read_picks_ensemble, get_network_stations, compute_matching_network_mask, generate_large_events_catalog)
 
 # pylint: disable=invalid-name, fixme, too-many-locals, too-many-statements
 # pylint: disable=attribute-defined-outside-init, logging-format-interpolation, logging-not-lazy
@@ -318,11 +315,13 @@ def _plot_network_relative_to_ref_station(df_plot, ref, target_stns, batch_optio
     :type display_options: class DisplayOptions
     """
     register_matplotlib_converters()
+    if df_plot is None:
+        return
     df_plot = df_plot.assign(relTtResidual=(df_plot['ttResidual'] - df_plot['ttResidualRef']))
 
     # Re-order columns
     df_plot = df_plot[['#eventID', 'originTimestamp', 'mag', 'originLon', 'originLat', 'originDepthKm',
-                       'net', 'sta', 'cha', 'pickTimestamp', 'phase', 'stationLon', 'stationLat',
+                       'net', 'sta', 'cha', 'pickTimestamp', 'stationLon', 'stationLat',
                        'distance', 'snr', 'ttResidual', 'ttResidualRef', 'relTtResidual',
                        'qualityMeasureCWT', 'qualityMeasureSlope', 'nSigma']]
 
@@ -704,7 +703,7 @@ def main(picks_file, network1, networks2, stations1=None, stations2=None,
     df_raw_picks = read_picks_ensemble(picks_file)
     # Remove unused columns
     df_raw_picks = df_raw_picks[['#eventID', 'originTimestamp', 'mag', 'originLon', 'originLat', 'originDepthKm',
-                                 'net', 'sta', 'cha', 'pickTimestamp', 'phase', 'stationLon', 'stationLat', 'az',
+                                 'net', 'sta', 'cha', 'pickTimestamp', 'stationLon', 'stationLat', 'az',
                                  'baz', 'distance', 'ttResidual', 'snr', 'qualityMeasureCWT', 'qualityMeasureSlope',
                                  'nSigma']]
     log.debug("Number of raw picks: {}".format(len(df_raw_picks)))

seismic/gps_corrections/requirementsVDI.txt

@@ -0,0 +1,31 @@
+# cd to hiperseis directory
+# module purge
+# module load openmpi
+# module load mpi4py
+# module load hdf5/1.10.5p
+# module load python3-as-python
+# alias python=python3
+# python -m venv venv
+# source venv/bin/activate
+# pip install -r seismic/gps_corrections/requirementsVDI.txt
+pyasdf
+numpy
+obspy
+pandas
+matplotlib
+ordered-set
+psutil
+click
+ujson
+sklearn
+netcdf4
+tqdm
+shapely
+descartes
+pyproj
+pytz
+pathlib2
+jupyter
+#  export PYTHONPATH=$PYTHONPATH:'pwd'
+#  python3 -m seismic.gps_corrections.gps_clock_correction_gui
+#  jupyter notebook

seismic/xcorqc/xcorr_station_clock_analysis.py

@@ -150,7 +150,7 @@ def do_spline_regression(self, group_ids, regression_degree):
             y = self.corrections_clean[mask_group]
             # Constrain the knot frequency to be proportional to the order, so that we don't overfit
             # to high frequency variations in the data just for the sake of lowering the spline residual.
-            t = np.linspace(x[0], x[-1], degree - 1)
+            t = np.linspace(x[0], x[-1], int(degree - 1))
             r = LSQUnivariateSpline(x, y, t[1:-1], k=degree)
             regressions[i] = r